@prefix n9j: <http://data.loterre.fr/ark:/67375/N9J> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix isothes: <http://purl.org/iso25964/skos-thes#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .

n9j:-HTZGLLK6-3
  skos:prefLabel "other techniques, theories, and tools"@en ;
  a skos:Concept ;
  skos:narrower n9j:-J8VGT8Q6-1 .

n9j:-methods
  a isothes:ConceptGroup ;
  skos:prefLabel "methods"@en ;
  skos:member n9j:-J8VGT8Q6-1 .

n9j: a skos:ConceptScheme .
n9j:-C4D7695V-N
  skos:prefLabel "artificial intelligence"@en ;
  a skos:Concept ;
  skos:narrower n9j:-J8VGT8Q6-1 .

n9j:-VN1S6M15-V
  skos:prefLabel "algorithms"@en ;
  a skos:Concept ;
  skos:narrower n9j:-J8VGT8Q6-1 .

n9j:-CR5H8Z3F-P
  skos:prefLabel "automated pattern recognition"@en ;
  a skos:Concept ;
  skos:narrower n9j:-J8VGT8Q6-1 .

n9j:-J8VGT8Q6-1
  skos:definition "Support vector machines (SVMs) are machine learning models that share some similarities with neural networks and logistic regression models for classification tasks. Examples of such tasks arise naturally in clinical settings, whenever one is given a set of data descriptors (e.g., lab results, clinical findings, imaging data, genetic information) and wants to predict health status or medical outcome given such data. [Source: Encyclopedia of Medical Decision Making; Support Vector Machines]"@en ;
  skos:broader n9j:-C4D7695V-N, n9j:-CR5H8Z3F-P, n9j:-VN1S6M15-V, n9j:-HTZGLLK6-3 ;
  skos:inScheme n9j: ;
  a skos:Concept ;
  owl:sameAs <https://concepts.sagepub.com/social-science/concept/support_vector_machines> ;
  skos:prefLabel "support vector machines"@en ;
  skos:exactMatch <https://id.nlm.nih.gov/mesh/D060388.html> .